scholarly journals Recommending Friends and Locations over a Heterogeneous Spatio-Temporal Graph

2015 ◽  
pp. 271-284
Author(s):  
Pavlos Kefalas ◽  
Panagiotis Symeonidis
Keyword(s):  
Temporal Graph ◽  
Spatio Temporal

Based on spatio-temporal graph convolution networks with residual connection for intelligence behavior recognition

2021 ◽  
pp. 002072092199660
Author(s):  
Yinong Zhang ◽  
Shanshan Guan ◽  
Cheng Xu ◽  
Hongzhe Liu
Keyword(s):  
Human Behavior ◽  
Behavior Recognition ◽  
Convolutional Network ◽  
Skeleton Model ◽  
Basic Technology ◽  
Temporal Model ◽  
Temporal Graph ◽  
Spatio Temporal ◽  
Human Behavior Recognition ◽  
Behavior Characteristics

In the era of intelligent education, human behavior recognition based on computer vision is an important branch of pattern recognition. Human behavior recognition is a basic technology in the fields of intelligent monitoring and human-computer interaction in education. The dynamic changes of human skeleton provide important information for the recognition of educational behavior. Traditional methods usually use manual information to label or traverse rules only, resulting in limited representation capabilities and poor generalization performance of the model. In this paper, a kind of dynamic skeleton model with residual is adopted—a spatio-temporal graph convolutional network based on residual connections, which not only overcomes the limitations of previous methods, but also can learn the spatio-temporal model from the skeleton data. In the big bone NTU-RGB + D dataset, the network model not only improved the representation ability of human behavior characteristics, but also improved the generalization ability, and achieved better recognition effect than the existing model. In addition, this paper also compares the results of behavior recognition on subsets of different joint points, and finds that spatial structure division have better effects.

scholarly journals Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction

2021 ◽  
Vol 30 ◽  
pp. 7760-7775
Author(s):  
Maosen Li ◽  
Siheng Chen ◽  
Yangheng Zhao ◽  
Ya Zhang ◽  
Yanfeng Wang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Motion Prediction ◽  
Temporal Graph ◽  
3D Skeleton ◽  
Spatio Temporal ◽  
Graph Neural Networks

scholarly journals Dynamic Adaptive Spatio-Temporal Graph Convolution for fMRI Modelling

2021 ◽  
pp. 125-134
Author(s):  
Ahmed El-Gazzar ◽  
Rajat Mani Thomas ◽  
Guido van Wingen
Keyword(s):  
Temporal Graph ◽  
Spatio Temporal

Data-Driven Time Series Forecasting for Social Studies Using Spatio-Temporal Graph Neural Networks

2021 ◽  
Author(s):  
Yi-Fan Li ◽  
Bo Dong ◽  
Latifur Khan ◽  
Bhavani Thuraisingham ◽  
Patrick T. Brandt ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Social Studies ◽  
Time Series Forecasting ◽  
Data Driven ◽  
Temporal Graph ◽  
Spatio Temporal ◽  
Graph Neural Networks

Distributed and parallel processing for real-time and dynamic spatio-temporal graph

2019 ◽  
Vol 23 (2) ◽  
pp. 905-926
Author(s):  
Junhua Fang ◽  
Jiafeng Ding ◽  
Pengpeng Zhao ◽  
Jiajie Xu ◽  
An Liu ◽  
...  
Keyword(s):  
Parallel Processing ◽  
Real Time ◽  
Temporal Graph ◽  
Spatio Temporal
Sign in / Sign up

Export Citation Format

Share Document